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Модель Мамфорда-Шаха сегментации графических изображений
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Language:
Russian
Keywords: сегментация изображений
In book
М.: МИЭМ НИУ ВШЭ, 2014.
Hamplová A., Lyavdansky A., Novák T. et al., CMES - Computer Modeling in Engineering and Sciences 2024 Vol. 140 No. 3 P. 2869–2889
This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions, employing two state-of-the-art deep learning algorithms, namely YOLOv8 and Roboflow 3.0. The goal is to contribute to the preservation and understanding of historical texts, showcasing the potential of modern deep learning methods in archaeological research. Our research culminates in several ...
Added: July 17, 2024
Пузаченко Ю. Г., Sandlerskiy R., Krenke A. et al., Russian Journal of Forest Science 2014 Vol. 7 No. 7 P. 838–854
The article proposes approaches to the use of multispectral remote information in basic research on the spatiotemporal organization of biogeocenotic cover with and without the use of ground field measurements. It is postulated that remote measurements reflect the biophysical condition of biogeocenotic cover defined by the absorption and conversion of solar energy and can be ...
Added: September 3, 2023
A. N. Krenke, R. B. Sandlersky, A. S. Baybar et al., Известия РАН. Серия биологическая. 2023 Vol. 50 No. 1 P. S85–S99
Four main models of the appearance of boundaries (in a particular case, integrity), arising from the theory of nonlinear dynamic systems, are considered briefly. On the basis of Kotelnikov’s fundamental sampling theorem and, accordingly, general information theory, the character of a distinguished boundary as a function of the sampling frequency in a spatial series with a ...
Added: December 2, 2022
Kirillov A., Gavrikov M., Lobacheva E. et al., , in: Proceedings of the 27th British Machine Vision Conference.: -, 2016. P. 1–12.
The Shape Boltzmann Machine (SBM) and its multilabel version MSBM have been recently introduced as deep generative models that capture the variations of an object shape. While being more flexible MSBM requires datasets with labeled parts of the objects for training. In the paper we present an algorithm for training MSBM using binary masks of ...
Added: February 24, 2017
Кириллов А. Н., Гавриков М. И., Lobacheva E. et al., Интеллектуальные системы. Теория и приложения 2015 Т. 19 № 2 С. 75–95
In this paper we consider the Shape Boltzmann Machine(SBM) and its multi-label version MSBM. We present an algorithm for training MSBM using only binary masks of objects and the seeds which approximately correspond to the locations of objects parts. ...
Added: September 30, 2015
Novikov N., В кн.: Сборник конкурсных работ смотра-конкурса научно-технического творчества студентов высших учебных заведений «Эврика-2009».: Лик, 2010. С. 41–43.
Сегментация изображений с использованием древовидной аппроксимации кластеров в многомерном признаковом пространстве ...
Added: December 3, 2013
Istratov A., Bulgakov S. A., В кн.: Фундаментальные и прикладные исследования, разработка и применение высоких технологий в промышленности и экономикеТ. 2: Высокие технологии, исследования, образование, экономика.: СПб.: Издательство Политехнического университета, 2012. Гл. 4 С. 18–22.
This paper represents results of research on image thresholding techniques.
Key words: image segmentation, image thresholding, otsu method, huang method, niblack method, triangle method. ...
Added: April 10, 2013